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Title: GitHub - Ewenwan/MachineLearning: Machine Learning in Action（机器学习实战） · GitHub

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Description: Machine Learning in Action（机器学习实战）. Contribute to Ewenwan/MachineLearning development by creating an account on GitHub.

Open Graph Description: Machine Learning in Action（机器学习实战）. Contribute to Ewenwan/MachineLearning development by creating an account on GitHub.

X Description: Machine Learning in Action（机器学习实战）. Contribute to Ewenwan/MachineLearning development by creating an account on GitHub.

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	https://github.com/Ewenwan/MachineLearning#machinelearning
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ApacheCN(apache中文网)	http://cwiki.apachecn.org/
【机器学习实战-中文版-带目录版.pdf】	https://github.com/apachecn/MachineLearning/tree/master/books
群小哥哥：Wizard Zhang	https://github.com/wizardforcel
《机器学习实战-ApacheCN.pdf》	https://github.com/apachecn/MachineLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98-ApacheCN.pdf
群小哥哥：红色石头的机器学习之路	https://github.com/RedstoneWill
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http://www.apachecn.org/organization/664.html	http://www.apachecn.org/organization/664.html
	https://github.com/Ewenwan/MachineLearning#机器学习
第 1 章: 机器学习基础	https://github.com/apachecn/MachineLearning/blob/master/docs/1.机器学习基础.md
@毛红动	https://github.com/ElmaDavies
第 2 章: KNN 近邻算法	https://github.com/apachecn/MachineLearning/blob/master/docs/2.k-近邻算法.md
@尤永江	https://github.com/youyj521
第 3 章: 决策树	https://github.com/apachecn/MachineLearning/blob/master/docs/3.决策树.md
@景涛	https://github.com/jingwangfei
第 4 章: 朴素贝叶斯	https://github.com/apachecn/MachineLearning/blob/master/docs/4.朴素贝叶斯.md
@wnma3mz	https://github.com/wnma3mz
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第 5 章: Logistic回归	https://github.com/apachecn/MachineLearning/blob/master/docs/5.Logistic回归.md
@微光同尘	https://github.com/DataMonk2017
第 6 章: SVM 支持向量机	https://github.com/apachecn/MachineLearning/blob/master/docs/6.支持向量机.md
@王德红	https://github.com/VPrincekin
第 7 章: 集成方法（随机森林和 AdaBoost）	https://github.com/apachecn/MachineLearning/blob/master/docs/7.集成方法-随机森林和AdaBoost.md
@片刻	https://github.com/jiangzhonglian
第 8 章: 回归	https://github.com/apachecn/MachineLearning/blob/master/docs/8.回归.md
@微光同尘	https://github.com/DataMonk2017
第 9 章: 树回归	https://github.com/apachecn/MachineLearning/blob/master/docs/9.树回归.md
@微光同尘	https://github.com/DataMonk2017
第 10 章: K-Means 聚类	https://github.com/apachecn/MachineLearning/blob/master/docs/10.k-means聚类.md
@徐昭清	https://github.com/xuzhaoqing
第 11 章: 利用 Apriori 算法进行关联分析	https://github.com/apachecn/MachineLearning/blob/master/docs/11.使用Apriori算法进行关联分析.md
@刘海飞	https://github.com/WindZQ
第 12 章: FP-growth 高效发现频繁项集	https://github.com/apachecn/MachineLearning/blob/master/docs/12.使用FP-growth算法来高效发现频繁项集.md
@程威	https://github.com/mikechengwei
第 13 章: 利用 PCA 来简化数据	https://github.com/apachecn/MachineLearning/blob/master/docs/13.利用PCA来简化数据.md
@廖立娟	https://github.com/lljuan330
第 14 章: 利用 SVD 来简化数据	https://github.com/apachecn/MachineLearning/blob/master/docs/14.利用SVD简化数据.md
@张俊皓	https://github.com/marsjhao
第 15 章: 大数据与 MapReduce	https://github.com/apachecn/MachineLearning/blob/master/docs/15.大数据与MapReduce.md
第 16 章: 推荐系统	https://github.com/apachecn/MachineLearning/blob/master/docs/16.推荐系统.md
	https://github.com/Ewenwan/MachineLearning#深度学习deeplearning--正在更新迭代
入门介绍	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/DeepLearning/1.%E5%85%A5%E9%97%A8%E4%BB%8B%E7%BB%8D.md
	https://github.com/Ewenwan/MachineLearning#自然语言处理nlp
	https://github.com/Ewenwan/MachineLearning#第一部分-入门介绍
自然语言处理入门介绍	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/1.%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86%E5%85%A5%E9%97%A8%E4%BB%8B%E7%BB%8D.md
	https://github.com/Ewenwan/MachineLearning#第二部分-机器翻译
机器翻译	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/2.%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91.md
	https://github.com/Ewenwan/MachineLearning#第三部分-篇章分析
篇章分析-内容概述	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/3.1.%E7%AF%87%E7%AB%A0%E5%88%86%E6%9E%90-%E5%86%85%E5%AE%B9%E6%A6%82%E8%BF%B0.md
篇章分析-内容标签	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/3.2.%E7%AF%87%E7%AB%A0%E5%88%86%E6%9E%90-%E5%86%85%E5%AE%B9%E6%A0%87%E7%AD%BE.md
篇章分析-情感分析	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/3.3.%E7%AF%87%E7%AB%A0%E5%88%86%E6%9E%90-%E6%83%85%E6%84%9F%E5%88%86%E6%9E%90.md
篇章分析-自动摘要	https://github.com/Ewenwan/MachineLearning/blob/dev/docs/NLP/3.4.%E7%AF%87%E7%AB%A0%E5%88%86%E6%9E%90-%E8%87%AA%E5%8A%A8%E6%91%98%E8%A6%81.md
	https://github.com/Ewenwan/MachineLearning#第四部分-unit-语言理解与交互技术
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	https://github.com/Ewenwan/MachineLearning#未来规划样子
机器学习基础	https://github.com/apachecn/MachineLearning/blob/master/docs/1.机器学习基础.md
@片刻	https://github.com/jiangzhonglian
KNN 近邻算法	https://github.com/apachecn/MachineLearning/blob/master/docs/2.k-近邻算法.md
@微光同尘	https://github.com/DataMonk2017
决策树	https://github.com/apachecn/MachineLearning/blob/master/docs/3.决策树.md
@景涛	https://github.com/jingwangfei
朴素贝叶斯	https://github.com/apachecn/MachineLearning/blob/master/docs/4.朴素贝叶斯.md
@wnma3mz	https://github.com/wnma3mz
@平淡的天	https://github.com/friedhelm739
Logistic回归	https://github.com/apachecn/MachineLearning/blob/master/docs/5.Logistic回归.md
@景涛	https://github.com/jingwangfei
SVM 支持向量机	https://github.com/apachecn/MachineLearning/blob/master/docs/6.支持向量机.md
@小王子	https://github.com/VPrincekin
@景涛	https://github.com/jingwangfei
集成方法	https://github.com/apachecn/MachineLearning/blob/master/docs/7.集成方法-随机森林和AdaBoost.md
@片刻	https://github.com/jiangzhonglian
随机森林	https://github.com/apachecn/MachineLearning/blob/master/docs/7.集成方法-随机森林和AdaBoost.md
@片刻	https://github.com/jiangzhonglian
AdaBoost	https://github.com/apachecn/MachineLearning/blob/master/docs/7.集成方法-随机森林和AdaBoost.md
@片刻	https://github.com/jiangzhonglian
回归	https://github.com/apachecn/MachineLearning/blob/master/docs/8.回归.md
@微光同尘	https://github.com/DataMonk2017
树回归	https://github.com/apachecn/MachineLearning/blob/master/docs/9.树回归.md
@微光同尘	https://github.com/DataMonk2017
@小王子	https://github.com/VPrincekin
K-Means 聚类	https://github.com/apachecn/MachineLearning/blob/master/docs/10.k-means聚类.md
@徐昭清	https://github.com/xuzhaoqing
利用 Apriori 算法进行关联分析	https://github.com/apachecn/MachineLearning/blob/master/docs/11.使用Apriori算法进行关联分析.md
@刘海飞	https://github.com/WindZQ
FP-growth 高效发现频繁项集	https://github.com/apachecn/MachineLearning/blob/master/docs/12.使用FP-growth算法来高效发现频繁项集.md
@程威	https://github.com/mikechengwei
利用 PCA 来简化数据	https://github.com/apachecn/MachineLearning/blob/master/docs/13.利用PCA来简化数据.md
@廖立娟	https://github.com/lljuan330
利用 SVD 来简化数据	https://github.com/apachecn/MachineLearning/blob/master/docs/14.利用SVD简化数据.md
@片刻	https://github.com/jiangzhonglian
@Lisanaaa	https://github.com/Lisanaaa
@咸鱼	https://github.com/Watermelon233
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NN	https://github.com/apachecn/MachineLearning/blob/master/docs/DeepLearning/1.入门介绍.md
@红色石头	https://github.com/RedstoneWill
@红色石头	https://github.com/RedstoneWill
@瑶妹	https://github.com/chenyyx
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@片刻	https://github.com/jiangzhonglian
@片刻	https://github.com/jiangzhonglian
@片刻	https://github.com/jiangzhonglian
Word2Vec 原理介绍	https://github.com/apachecn/MachineLearning/blob/master/docs/NLP/Word2Vec.md
@片刻	https://github.com/jiangzhonglian
大数据与MapReduce	https://github.com/apachecn/MachineLearning/blob/master/docs/15.大数据与MapReduce.md
推荐系统	https://github.com/apachecn/MachineLearning/blob/master/docs/16.推荐系统.md
	https://github.com/Ewenwan/MachineLearning#项目负责人
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@那伊抹微笑	https://github.com/wangyangting
@瑶妹	https://github.com/chenyyx
2017-04-08_第一期的总结	https://github.com/Ewenwan/MachineLearning/blob/dev/report/2017-04-08_%E7%AC%AC%E4%B8%80%E6%9C%9F%E7%9A%84%E6%80%BB%E7%BB%93.md
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	https://github.com/Ewenwan/MachineLearning#项目贡献者
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@Veyron C	https://github.com/caopeirui
@Cugtyt	https://github.com/Cugtyt
@BBruceyuan	https://github.com/hey-bruce
ApacheCN(apache中文网) 维护更新	http://www.apachecn.org
关于我们	http://cwiki.apachecn.org/pages/viewpage.action?pageId=2887240
加入我们	http://cwiki.apachecn.org/pages/viewpage.action?pageId=2887239
	https://github.com/Ewenwan/MachineLearning#网站视频
知乎问答-爆炸啦-机器学习该怎么入门？	https://www.zhihu.com/question/20691338/answer/248678328
MachineLearning(机器学习) 学习路线图	http://www.apachecn.org/map/145.html
	https://github.com/Ewenwan/MachineLearning/blob/dev/images/MainPage/ApacheCN-ML-bilibili-compare.jpg
《机器学习实战-教学版》	https://space.bilibili.com/97678687/#!/channel/detail?cid=22486
《机器学习实战-讨论版》	https://space.bilibili.com/97678687/#!/channel/detail?cid=13045
机器学习初学者建议 \| ApacheCN	http://www.apachecn.org/map/179.html
MachineLearning(机器学习) 学习路线图	http://www.apachecn.org/map/145.html
	http://www.acfun.cn/u/12540256.aspx#page=1
	https://space.bilibili.com/97678687/#!/channel/index
	http://i.youku.com/apachecn
	http://study.163.com/course/courseMain.htm?courseId=1004582003
	https://github.com/Ewenwan/MachineLearning#免责声明
ApacheCN 组织资源	http://www.apachecn.org/
	https://github.com/Ewenwan/MachineLearning#apachecn-组织资源
kaggle: 机器学习竞赛	https://github.com/apachecn/kaggle
TensorFlow R1.2 中文文档	http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030122
机器学习实战-教学	https://github.com/apachecn/MachineLearning
Spark 2.2.0和2.0.2 中文文档	http://spark.apachecn.org/
Zeppelin 0.7.2 中文文档	http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030467
Pytorch 0.3 中文文档	http://pytorch.apachecn.org/cn/0.3.0/
Sklearn 0.19 中文文档	http://sklearn.apachecn.org/
Storm 1.1.0和1.0.1 中文文档	http://storm.apachecn.org/
Kibana 5.2 中文文档	http://cwiki.apachecn.org/pages/viewpage.action?pageId=8159377
LightGBM 中文文档	http://lightgbm.apachecn.org/cn/latest
Kudu 1.4.0 中文文档	http://cwiki.apachecn.org/pages/viewpage.action?pageId=10813594
XGBoost 中文文档	http://xgboost.apachecn.org/cn/latest
Elasticsearch 5.4 中文文档	http://cwiki.apachecn.org/pages/viewpage.action?pageId=4260364
Beam 中文文档	http://beam.apachecn.org/
ml.apachecn.org/mlia	http://ml.apachecn.org/mlia
Readme	https://github.com/Ewenwan/MachineLearning#readme-ov-file
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Releases	https://github.com/Ewenwan/MachineLearning/releases
2 tags	https://github.com/Ewenwan/MachineLearning/tags
Packages 0	https://github.com/users/Ewenwan/packages?repo_name=MachineLearning
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